Performance-based system reliability analysis for steel moment frames

Abstract

This study aims to bridge the gap between two major design philosophies in structural design: load and resistance factor design (LRFD) and performance-based design (PBD). While LRFD prioritizes the design of structural members, PBD starts by controlling the system's target parameter. The main area for improvement of LRFD is paying attention to the structure's performance. At the same time, PBD needs to pay attention to the sufficiency of internal members in the presence of local damages. To bring these two attitudes closer together, the study proposes a system-reliability-performance-based design analysis to simultaneously measure the entire structure's safety level associated with the reliability of elements. As a state-of-the-art, new performance-based limit state functions are introduced to measure structural reliability indices corresponding to desired performance levels. Multi-story frames were designed and evaluated based on incremental dynamic analysis. The entire structure was designed and controlled using the linear static analysis method, and static and dynamic nonlinear analyzes were performed to evaluate its behavior. Dynamic analysis of acceleration mapping was also performed to investigate the performance of the structural components. The proposed combined design algorithm aims to develop a new set of performance-based load combinations and provide a strong interlock between LRFD and PBD. The study's results show that the IO level has the lowest performance-based system reliability index, while the CP level has the highest. It was observed that as the number of story levels increases, the performance-based system reliability index decreases due to an upsurge in the possibility of failure patterns. Therefore, the current LRFD practices are unlikely to provide the IO's perfect reliable level for the entire system. The study concludes that the new approach can enhance the safety of structures and prevent catastrophic failure.